Chemical profiling of white (Tirmania nivea) and black (Terfezia claveryi) desert truffles using UPLC-MS/MS analysis followed by their discrimination based on their anti-inflammatory biomarkers identified using chemometrics and network pharmacology-based analysis was attempted. 25 compounds were identified using UPLC/MS/MS analysis in the extracts of T. claveryi and T. nivea belonging to saturated and unsaturated fatty acids, phenolic acids, alkanes and carboxylic acids. Identified compounds were forwarded to network-pharmacology-based analysis which revealed that resveratrol, oleic acid, margaric acid, naringenin, behenic acid and lauric acid were the top hit compounds related to anti-inflammatory targets. In-vitro anti-inflammatory testing assessed on LPS-stimulated WBCs revealed that T. claveryi and T. nivea extracts reduced TNF-α to the levels of 32 pg/ml and 55 pg/ml, IL-1β level to 55 and 85 pg/ml, and IFN-γ level to 130 nmol/ml and 175 nmol/ml, respectively. Further, the constructed orthogonal projection to latent structures discriminant analysis (OPLS-DA) model coefficients indicated that T. claveryi exhibited its in-vitro anti-inflammatory activity through down regulation of TNF-α pro-inflammatory markers with margaric acid, oleic acid, naringenin and resveratrol being its biomarkers while T. nivea affected mainly IL-1β and IFN-γ pro-inflammatory markers levels with behenic acid, lauric acid, caffeic acid and docosatetraenoic acid being its chemical markers.
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